中文摘要：

新疆克拉玛依油田砾岩油藏经过40年的注水开发，目前已进入高含水开发阶段，准确识别水淹层、定量划分水淹级别已经成为老区油藏开发调整的重点和难点。以克拉玛依油田六中区克下组砾岩油藏为研究对象，利用2006年重点调整的3口密闭取心井的岩心资料，结合砾岩油藏的实际地质特点，分析了砾岩油藏各种储层参数的影响因素。选择符合砾岩油藏地质特征和开发规律的测井曲线，基于交会图和多元线性回归的方法，建立了六中区克下组物性、岩性、产水率以及水驱指数等各种解释模型，并从中提取出产水率、含油饱和度和水驱指数3个水淹特征参数。以3个参数为定量判断水淹级别的主要依据，结合水淹层电阻率的定性识别图版，制定了砾岩油藏水淹层定量识别的规则和方法。以上技术应用到六中区克下组实际的水淹层解释中，综合解释符合率为84．36％，达到了实际解释的精度，最终形成了一套砾岩油藏水淹层定量识别的评价转术撂高了水淹层的解释精度和符合率。

英文摘要：

The conglomerate reservoirs in Karamay Oilfield have entered the development phase of high water-cut after forty years of waterflooding. An accurate identification of water-flooded zones as well as a quantitative classification of watering-out level is the key and difficult issue to be considered in the adjustment of development strategy in this maturing oilfield. This paper documents a study that takes the conglomerate reservoirs in the Kex- ia Formation of the Liuzhong block as an example. It analyzes factors that affect the reservoir parameters by using the pressure coring data of three wells that were the focus of development adjustment in 2006 and by combining the actual geological characteristics of conglomerate reservoirs. It also selects logs that match well with the geo- logical characteristics and production pattern of the conglomerate reservoirs. Models for the interpretation of physical properties,lithology,water production rate, and water drive index of the Kexia Formation are estab- lished based on methods like cross plotting and muhivariate linear regression. Three parameters, namely the water production rate, the oil saturation, and the water drive index, are chosen to be the main factors for aquan- titative determination of watering-out level. Combining these factors with qualitative resistivity-identification chart for watered-out zones, the study offers rules and methods for qualitative identification of watered-out zones in this kind of reservoirs. The application of the method to the Kexia Formation yielded a coincidence rate of as high as 84. 36%, well beyond the required accuracy. A set of technologies for quantitative identification of watered-out zones in conglomerate reservoirs is finally developed to improve the accuracy of watered-out zone identification.